Net primary productivity and spatial distribution of vegetation in an alpine wetland, Qinghai-Tibetan Plateau

To initially describe vegetation structure and spatial variation in plant biomass in a typical alpine wetland of the Qinghai-Tibetan Plateau, net primary productivity and vegetation in relationship to environmental factors were investigated. In 2002, the wetland remained flooded to an average water depth of 25 cm during the growing season, from July to mid-September. We mapped the floodline and vegetation distribution using GPS (global positioning system). Coverage of vegetation in the wetland was 100%, and the vegetation was zonally distributed along a water depth gradient, with three emergent plant zones (Hippuris vulgaris-dominated zone, Scirpus distigmaticus-dominated zone, and Carex allivescers-dominated zone) and one submerged plant zone (Potamogeton pectinatus-dominated zone). Both aboveground and belowground biomass varied temporally within and among the vegetation zones. Further, net primary productivity (NPP) as estimated by peak biomass also differed among the vegetation zones; aboveground NPP was highest in the Carex-dominated zone with shallowest water and lowest in the Potamogeton zone with deepest water. The area occupied by each zone was 73.5% for P. pectinatus, 2.6% for H. vulgaris, 20.5% for S. distigmaticus, and 3.4% for C. allivescers. Morphological features in relationship to gas-transport efficiency of the aerial part differed among the emergent plants. Of the three emergent plants, H. vulgaris, which dominated in the deeper water, showed greater morphological adaptability to deep water than the other two emergent plants.

Effects of altitude on plant-species diversity and productivity in an alpine meadow, Qinghai-Tibetan plateau

During the growing seasons of 2002 and 2003, biomass productivity and diversity were examined along an altitudinal transect on the south-western slope of Beishan Mountain, Maqin County (33 degrees 43'-35 degrees 16'N, 98 degrees 48'-100 degrees 55'E), Qinghai-Tibetan Plateau. Six altitudes were selected, between 3840 and 4435 m. Soil organic matter, soil available N and P and environmental factors significantly affected plant-species diversity and productivity of the alpine meadows. Aboveground biomass declined significantly with increasing altitude (P < 0.05) and it was positively and linearly related to late summer soil-surface temperature. Belowground biomass (0 - 10-cm depth) was significantly greater at the lowest and highest altitudes than at intermediate locations, associated with water and nutrient availabilities. At each site, the maximum belowground biomass values occurred at the beginning and the end of the growing seasons (P < 0.05). Soil organic matter content, and available N and P were negatively and closely related to plant diversity (species richness, Shannon-Wiener diversity index, and Pielou evenness index).

Effect of N fertilizer on the productivity and nutritive values of perennial grass mixtures in the alpine region of Qinghai-Tibetan Plateau, China

A study was conducted on grass mixtures that included smooth bromegrass (SB) + drooping wild ryegrass (DW), smooth bromegrass + Siberian wild ryegrass (SW) + crested wheatgrass (CW) and smooth bromegrass + Siberian wild ryegrass + drooping wild ryegrass + crested wheatgrass in the alpine region of Qinghai-Tibetan Plateau. The study was conducted from 1998 to 2000 to investigate the effects of N application rates and growing year on herbage dry matter (DM) yield and nutritive values. Herbage DM production increased linearly with N application rates. The effect of N application on DM yields was greater (P < 0.05) in the 2nd and 3rd production years than in the establishment year. Dry matter yields of SB + SW + CW and SB + SW + DW + CW can reach as high as 15 000 kg ha(-1) at 345 kg ha(-1) N rate in the 3rd growing year. With increased N application rates, crude protein (CP) contents and 48 h in sacco DM degradability of grasses increased (P < 0.05). No effect (P > 0.05) of N application was detected on organic matter (OM) and acid detergent fibre (ADF) concentration. It can be concluded that for increased biomass production in the alpine region of the Qinghai-Tibetan Plateau, a minimum of 345 kg N ha(-1) should be applied to grass stands in three split application of 115 kg N ha(-1), in early June, early July and late July

Productivity and persistence of perennial grass mixtures under competition from annual weeds in the alpine region of the Qinghai-Tibetan Plateau

In the alpine region of the Qinghai-Tibetan Plateau four indigenous perennial grass species Bromus inermis (BI), Elymus sibiricus (ES), Elymus nutans (EN) and Agropyron cristatum (AC) were cultivated as three mixtures with different compositions and seeding rates, BI + EN, BI + ES + AC and BI + ES + EN + AC. From 1998 to 2001 there were three different weeding treatments: never weeded (CK); weeded on three occasions in the first year (1-y) and weeded on three occasions in both the first and second year (2-y) and their effect of grass combination and interactions on sward productivity and persistence was measured. Intense competitive interference by weedy annuals reduced dry matter (DM) yield of the swards. Grass combination significantly affected sward DM yields, leaf area index (LAI) and foliar canopy cover and also species composition DM and LAI, and species plant cover. Interaction between weeding treatments and grass combination was significant for sward DM yield, LAI and canopy cover, but not on species composition for DM, LAI or species plant cover. Grass mixture BI + ES + EN + AC gave the highest sward DM yield and LAI for both weeding and non-weeding treatments. Species ES and EN were competitively superior to the others. Annual weedy forbs must be controlled to obtain productive and stable mixtures of perennial grasses, and germination/emergence is the most important time for removal. Weeding three times (late May, late June and mid-July) in the establishment year is enough to maintain the production and persistence of perennial grass mixtures in the following growing seasons. Extra weeding three times in the second growing year makes only a slight improvement in productivity.

砂泥岩储层测井产能预测方法研究

Productivity prediction is very important in the exploration and development of oilfields. Using well log data to predict productivity is a front-line technology， which is key issue in petroleum exploration phase. The essential factors of productivity prediction is building practical models and correcting various causes to improve precision of prediction parameters. Any errors of parameters selections can affect the calculation of productivity prediction; therefore， how to improve research means and calculation accuracy is an important task of productivity prediction. Theory and case examples are deeply and comprehensively studied in the paper. Based on the theory of mud-filtrate invasion and experimental results， the damage of drilling， cementing， perforating，acidizing and fracturing were investigated. The damage depth was quantitatively evaluated by log data， based on this， the processing results of reservoir sensitivity were used to analysis quantitatively the damage of reservoir. The productivity prediction and reservoir damage were initiatively incorporated according to well logging， and the precision of productivity prediction was effectively improved. The method of NMR was explored to calculate the fluid viscosity on the basis of reservoir physical method， and the differences between the two methods were compared in the paper. From the theory fluid flow in porous media， various of theoretical models of production prediction were explored and several practical models were consided， such as productivity index method， improved productivity index method， improved Bearder method， SVM and so on. The characteristic and the application scope of these methods were studied. The inflow productivity and outflow productivity were incorporated and nodal analysis method was used to forecast wellhead yield， thus achieved scientifically production. On the applied background of conventional logging suite， the applying of special items or new logging method which is practical in the research area were studied， the logging suite was further optimized， and the precision of forecast was improved. On the basis of the modeling and the calculation of parameters， these methods were verified and analyzed， and the reconstruct principle was also built for block reservoir. The research block was processed by these methods and compared with testing data. Based on above the research， a technological system which is practical for shaly sand profiles in Shengli Oilfield was built. The system can reach commercialized degree，and satisfied the need of exploration and development of the oilfield.

鄂尔多斯盆地上古生界低渗透砂岩有效储层识别与预测

Sulige Gasfield, with a basically proven reserve as high as one trillion cubic meters, is one giant gas field discovered in China. The major gas -bearing layers are Upper Paleozoic strata with fluvial-lacustrine sedimentary facies. Generally, gas reservoirs in this field are characteristic by "five low" properties, namely low porosity, low permeability, low formation pressure, low productivity and low gas abundance. Reservoirs in this field also feature in a large distribution area, thin single sandbody thickness, poor reservoir physical properties, thin effective reservoir thickness, sharp horizontal and/or vertical changes in reservoir properties as well as poor connectivity between different reservoirs. Although outstanding achievements have been acquired in this field, there are still several problems in the evaluation and development of the reservoirs, such as: the relation between seismic attributes and reservoir property parameters is not exclusive, which yields more than one solution in using seismic attributes to predict reservoir parameters; the wave impedance distribution ranges of sandstone and mudstone are overlapped, means it is impossible to distinguish them through the application of post-stack impedance inversion; studies on seismic petrophysics, reservoir geophysical properties, wave reflection models and AVO features have a poor foundation, makes it difficult to recognize the specific differences between tight sandstone and gas-bearing sandstone and their distribution laws. These are the main reasons causing the low well drilling success rate and poor economic returns, which usually result in ineffective development and utilization of the field. Therefore, it is of great importance to perform studies on identification and prediction of effective reservoirs in low permeable sandstone strata. Taking the 2D and 3D multiwave-multicomponent seismic exploration block in Su6-Su5 area of Sulige field as a study area and He 8 member as target bed, analysis of the target bed sedimentary characteristics and logging data properties are performed, while criteria to identify effective reservoirs are determined. Then, techniques and technologies such as pre-stack seismic information (AVO, elastic impedance, wave-let absorption attenuation) and Gamma inversion, reservoir litological and geophysical properties prediction are used to increase the precision in identifying and predicting effective reservoirs; while P-wave and S-wave impedance, ratio of P/S wave velocities, rock elastic parameters and elastic impedance are used to perform sandstone gas-bearing property identification and gas reservoir thickness prediction. Innovative achievements are summarized as follows: 1. The study of this thesis is the first time that multiwave-multicomponent seismic data are used to identify and predict non-marine classic reservoirs in China. Through the application of multiwave-multicomponents seismic data and integration of both pre-stack and post-stack seismic data, a set of workflows and methods to perform high-precision prediction of effective reservoirs in low permeable sandstone is established systematically. 2. Four key techniques to perform effective reservoir prediction including AVO analysis, pre-stack elastic wave impedance inversion, elastic parameters inversion, and absorption attenuation analysis are developed, utilizing pre-stack seismic data to the utmost and increasing the correct rate for effective reservoir prediction to 83% from the former 67% with routine methods. 3. This thesis summarizes techniques and technologies used in the identification reservoir gas-bearing properties using multiwave-multicomponent seismic data. And for the first time, quantitative analysis on reservoir fluids such as oil, gas, and/or water are carried out, and characteristic lithology prediction techniques through the integration of pre-stack and post-stack seismic prediction techniques, common seismic inversion and rock elastic parameters inversion, as well as P-wave inversion and converted wave inversion is put forward, further increasing the correct rate of effective reservoir prediction in this area to 90%. 4. Ten seismic attribute parameters are selected in the 3D multi-wave area to perform a comprehensive evaluation on effective reservoirs using weighted-factor method. The results show that the first class effective reservoir covers an area of 10.08% of the study area, while the second and the third class reservoirs take 43.8% and 46% respectively, sharply increasing the success rate for appraisal and development wells.